Design and Development of a Hybrid Eye and Mobile Controlled Wheelchair Prototype using Haar cascade Classifier: A Proof of Concept
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Date
2023-08
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Publisher
Springer Nature Switzerland
Abstract
According to the wheelchair foundation, about 1.86% of the world’s
population requires a functional wheelchair. Most of these wheelchairs have manual
control systems which puts millions of people with total paralyzes (total loss
of muscle control including the head) at a disadvantage. However, the majority
of those who suffer from muscular and neurological disorders still retain the
ability to move their eyes. Hence the concept of eye-controlled wheelchair. This
paper focused on the design and development of a hybrid control system (eye and
mobile interface) for a wheelchair prototype as a proof of concept. The systemwas
implemented using the pre-trained Haar cascade ML classifier in open CV. Focus
was shifted from high accuracy common to lab-based studies to deployment and
power consumption which are critical to usability. The system consists of a motor
chassis that takes the place of a wheelchair, a raspberry pi4 module which acts
as a mini-computer for image and information processing, and a laser sensor to
achieve obstacle avoidance. The Bluetooth module enables serial communication
between the motor chassis and the raspberry pi, while the power supply feeds the
raspberry pi and the camera. The system performance evaluation was carried out
using obstacle avoidance and navigation tests. An accuracy of 100% and 89%
were achieved for obstacle avoidance and navigation, respectively, which shows
that the system would be helpful for wheelchair users facing autonomous mobility
issues.
Description
Keywords
Paralysis · Wheelchair · Eye control · Obstacles avoidance · Camera